MPP: Multiscale Path Planning for UGV Navigation in Semi-structured Environments

Autonomous navigation of unmanned ground vehicles (UGVs) in structured road and indoor environments has made significant progress in recent years. However, navigation in outdoor semi-structured environments remains a challenge. This paper presents the multiscale path planning (MPP) method for UGV navigation in semi-structured environments. MPP leverages global, mid-layer and local planners to obtain global path and handle local obstacles of different sizes. First, the global planner provides guidance based on road connection relationships, selecting optimal connections by evaluating the distance between road nodes. Next, the mid-layer planner perceives large-scale obstacles and constructs the costmap, generating a mid-layer path that offers a general direction for the UGV. Finally, a local trajectory planning algorithm, namely terrain-considering timed elastic band (TC-TEB), is used to obtain local trajectory. This algorithm incorporates terrain-velocity constraints into the TEB algorithm to ensure the vehicle’s vertical stability. We demonstrate the safety and effectiveness of MPP through experiments in both simulated and real-world environments.

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Publication Details

Published
2024-10-14
DOI
https://doi.org/10.1109/iros58592.2024.10801877
Citations
2
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.50

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MPP: Multiscale Path Planning for UGV Navigation in Semi-structured Environments

Ran Song, Zhiqiang Yang, Wei Zhang, Ruifeng Wang et al.
2 citations
Robotic Path Planning Algorithms
0.50
article

MPP: Multiscale Path Planning for UGV Navigation in Semi-structured Environments

Ran Song, Zhiqiang Yang, Wei Zhang, Ruifeng Wang, Rui Cao, Ziyu Meng
article en
2 citations

Abstract

Autonomous navigation of unmanned ground vehicles (UGVs) in structured road and indoor environments has made significant progress in recent years. However, navigation in outdoor semi-structured environments remains a challenge. This paper presents the multiscale path planning (MPP) method for UGV navigation in semi-structured environments. MPP leverages global, mid-layer and local planners to obtain global path and handle local obstacles of different sizes. First, the global planner provides guidance based on road connection relationships, selecting optimal connections by evaluating the distance between road nodes. Next, the mid-layer planner perceives large-scale obstacles and constructs the costmap, generating a mid-layer path that offers a general direction for the UGV. Finally, a local trajectory planning algorithm, namely terrain-considering timed elastic band (TC-TEB), is used to obtain local trajectory. This algorithm incorporates terrain-velocity constraints into the TEB algorithm to ensure the vehicle’s vertical stability. We demonstrate the safety and effectiveness of MPP through experiments in both simulated and real-world environments.

Shandong University (CN)
National Natural Science Foundation of China, Young Scientists Fund, Research and Development
Openalex Percentile: Top 32%
Robotic Path Planning Algorithms
0.50
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